Cerebral Palsy (CP) is the most common motor disorder in children, affecting more than 3 in every 1000 children in the United States. Impaired gait is one of the most debilitating effects of CP. The current standard for measuring movement impairment in the outpatient clinic involves use of instruments that cannot quantify movement accurately and may be administered differently depending on the user's expertise. Instrumented gait analysis (IGA) is the most common quantitative method used for clinical gait assessment. The technique is laboratory based and most commonly uses optical motion capture to characterize the kinematics of motion. These systems are the industry gold standard, but they are costly, cumbersome, may suffer from optical occlusion, and because they require a dedicated motion laboratory with specialists to collect, process and interpret movement data, are not easily integrated into the outpatient clinic. Thus, there is a need for a portable, easy to use system to provide objective measurements of gait that are critical for rehabilitation therapy and surgical planning for children with functional limitations associated with CP and other movement disorders. The objective of this project is to develop and determine the feasibility of a wearable system called IMove to easily and accurately characterize and assess gait in children with CP. IMove will use patented, wearable inertial sensors developed and commercialized by our company, APDM. The system will provide joint kinematics and temporal- spatial measures of gait similar to those obtained by optical motion capture systems. Furthermore, IMove will be portable, unobtrusive, easy to use, and requires no lengthy setup or calibration; all of which makes the proposed system well suited for use in the clinic to improve clinicians' decision-making around diagnosis, prognosis and treatment monitoring. We hypothesize that it is feasible to use IMove to measure normal and abnormal gait metrics that are clinically important for CP. These metrics include kinematic measurements of pelvic, hip, knee and ankle joint angles during gait. IMove will also provide temporal-spatial measures of asymmetry of swing duration due to leg muscle spasticity, and variability of step length and duration. The long-term impact of this technology will be better clinical decisions that are more accessible to the disabled population than current methods of gait analysis. This will result in improved diagnosis, therapeutic interventions, individualized rehabilitation strategies, referrals for alternative interventions, and sensitive clinical trial outcome measures that can be performed in most outpatient clinics rather than specialized laboratory settings. This Phase I project will demonstrate the validity and clinical feasibility of IMove, which will justify the investment necessary to develop and commercialize IMove in Phase II. This project has two specific aims: AIM I. Develop IMove to detect the stance and swing phase of gait cycles and to characterize pelvic, hip, knee and ankle joint angles during these phases. The algorithm will utilize wirelessly synchronized inertial sensors attached to the pelvis, femur, tibia and foot to continuously quantify the joint angles, characterize their coordination during the critical temporal events of te gait cycle. Milestone 1: Develop a recursive Bayesian tracking algorithm to measure the joint angles of the lower limb during gait using wearable inertial sensors. AIM II. Validate measures obtained from IMove with those obtained from a motion capture system. We hypothesize that IMove will accurately detect stance and swing phases and track the pelvic, hip, knee and ankle joint angles during gait. Milestone 2: To test this hypothesis, we will compare the IMove metrics with those obtained from a motion capture system in 18 children with CP and 18 age-matched typically developing children.